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SEON is a fraud prevention and AML compliance platform serving thousands of companies globally, including Revolut, Wise, and Bilt. The company uses 900+ real-time, first-party data signals to enrich customer profiles, flag suspicious behavior, and streamline compliance workflows.
You will join the ID Verification ML team as a Software Engineer, acting as the bridge between ML research and production-grade software. This is a hands-on role combining strong software engineering with machine learning infrastructure work.
Key responsibilities:
- Contribute to building in-house ML solutions for ID verification
- Deliver high-quality NodeJS, TypeScript, and Python code with focus on simplicity, performance, and scalability
- Design, build, and maintain ETL/data pipelines that transform raw data into clean, labeled, versioned training datasets
- Build and operate data-intensive backend services across training and evaluation workflows
- Support ML model packaging, delivery, and serving into production
- Partner closely with ML engineers to translate research prototypes into production-ready code
- Provide technical expertise through code review and help raise engineering standards across the team
- Design technical implementations, break down features into development stories, and provide estimates
- Mentor colleagues and foster continuous learning
- Participate in hiring interviews and technical assessments
- Handle sensitive data with rigor, ensuring data residency and compliance are first-class engineering concerns
Requirements:
- 5+ years of software engineering experience with NodeJS, TypeScript, React, Python, REST APIs, RDBMS, and NoSQL
- Comfort operating in a research-adjacent, evidence-driven environment
- Passion for building scalable data pipelines that empower ML engineering
- Agile and iterative mindset with end-to-end ownership mentality
- Experience with cloud data/ML infrastructure (AWS preferred)
- Experience with containerization (Docker) and Kubernetes
- Understanding of data modeling across relational and unstructured data
- Strong automated testing experience
- Excellent problem-solving skills
- English language proficiency
